Quentin Macé

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upvoted a collection about 1 month ago

ViDoRe Benchmark V3

Collection

ViDoRe V3 is our latest benchmark, engineered to set a new industry gold standard for multi-modal, enterprise document retrieval evaluation. • 8 items • Updated Nov 5 • 12

upvoted an article about 1 month ago

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Article

ViDoRe V3: a comprehensive evaluation of retrieval for enterprise use-cases

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Nov 5

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53

upvoted a paper 2 months ago

ModernVBERT: Towards Smaller Visual Document Retrievers

Paper • 2510.01149 • Published Oct 1 • 30

upvoted 2 articles 2 months ago

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Article

ModernVBERT: Towards Smaller Visual Document Retrievers

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Oct 3

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44

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Article

Introducing RTEB: A New Standard for Retrieval Evaluation

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• +4

Oct 1

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128

upvoted an article 4 months ago

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Article

Luth: Efficient French Specialization for Small Language Models

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Aug 11

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18

upvoted 2 articles 5 months ago

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Article

Introducing ColQwen-Omni: Retrieve in every modality

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Jul 17

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75

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Article

Should We Still Pretrain Encoders with Masked Language Modeling?

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Jul 2

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21

upvoted a paper 5 months ago

Should We Still Pretrain Encoders with Masked Language Modeling?

Paper • 2507.00994 • Published Jul 1 • 79

upvoted 2 articles 9 months ago

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Article

DeepSearch Using Visual RAG in Agentic Frameworks 🔎

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Mar 21

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37

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Article

ViDoRe Benchmark V2: Raising the Bar for Visual Retrieval

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Mar 18

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13